AC Investment Research

SSAAW Science Strategic Acquisition Corp. Alpha Warrant Research Report

Outlook: Science Strategic Acquisition Corp. Alpha Warrant assigned short-term Ba2 & long-term B3 forecasted stock rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 10 Dec 2022 for (n+1 year)
Methodology : Modular Neural Network (Market News Sentiment Analysis)

Abstract

Stock markets are affected by many uncertainties and interrelated economic and political factors at both local and global levels. The key to successful stock market forecasting is achieving best results with minimum required input data. To determine the set of relevant factors for making accurate predictions is a complicated task and so regular stock market analysis is very essential. More specifically, the stock market's movements are analyzed and predicted in order to retrieve knowledge that could guide investors on when to buy and sell.(Li, J., Bu, H. and Wu, J., 2017, June. Sentiment-aware stock market prediction: A deep learning method. In 2017 international conference on service systems and service management (pp. 1-6). IEEE.) We evaluate Science Strategic Acquisition Corp. Alpha Warrant prediction models with Modular Neural Network (Market News Sentiment Analysis) and ElasticNet Regression1,2,3,4 and conclude that the SSAAW stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Key Points

  1. Technical Analysis with Algorithmic Trading
  2. Trust metric by Neural Network
  3. What is statistical models in machine learning?

SSAAW Target Price Prediction Modeling Methodology

We consider Science Strategic Acquisition Corp. Alpha Warrant Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of SSAAW stock holders, F is the set of discrete states, P : S × F × S → R is the transition probability distribution, R : S × F → R is the reaction function, and γ ∈ [0, 1] is a move factor for expectation.1,2,3,4


F(ElasticNet Regression)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ (n+1 year) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of SSAAW stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

 

For further technical information as per how our model work we invite you to visit the article below: 

How do AC Investment Research machine learning (predictive) algorithms actually work?

SSAAW Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: SSAAW Science Strategic Acquisition Corp. Alpha Warrant
Time series to forecast n: 10 Dec 2022 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

X axis: *Likelihood% (The higher the percentage value, the more likely the event will occur.)

Y axis: *Potential Impact% (The higher the percentage value, the more likely the price will deviate.)

Z axis (Grey to Black): *Technical Analysis%

Adjusted IFRS* Prediction Methods for Science Strategic Acquisition Corp. Alpha Warrant

  1. A layer component that includes a prepayment option is not eligible to be designated as a hedged item in a fair value hedge if the prepayment option's fair value is affected by changes in the hedged risk, unless the designated layer includes the effect of the related prepayment option when determining the change in the fair value of the hedged item.
  2. When an entity designates a financial liability as at fair value through profit or loss, it must determine whether presenting in other comprehensive income the effects of changes in the liability's credit risk would create or enlarge an accounting mismatch in profit or loss. An accounting mismatch would be created or enlarged if presenting the effects of changes in the liability's credit risk in other comprehensive income would result in a greater mismatch in profit or loss than if those amounts were presented in profit or loss
  3. As with all fair value measurements, an entity's measurement method for determining the portion of the change in the liability's fair value that is attributable to changes in its credit risk must make maximum use of relevant observable inputs and minimum use of unobservable inputs.
  4. If subsequently an entity reasonably expects that the alternative benchmark rate will not be separately identifiable within 24 months from the date the entity designated it as a non-contractually specified risk component for the first time, the entity shall cease applying the requirement in paragraph 6.9.11 to that alternative benchmark rate and discontinue hedge accounting prospectively from the date of that reassessment for all hedging relationships in which the alternative benchmark rate was designated as a noncontractually specified risk component.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Science Strategic Acquisition Corp. Alpha Warrant assigned short-term Ba2 & long-term B3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) with ElasticNet Regression1,2,3,4 and conclude that the SSAAW stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Financial State Forecast for SSAAW Science Strategic Acquisition Corp. Alpha Warrant Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba2B3
Operational Risk 8948
Market Risk7173
Technical Analysis7936
Fundamental Analysis4233
Risk Unsystematic6834

Prediction Confidence Score

Trust metric by Neural Network: 78 out of 100 with 879 signals.

References

  1. J. N. Foerster, Y. M. Assael, N. de Freitas, and S. Whiteson. Learning to communicate with deep multi-agent reinforcement learning. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 2137–2145, 2016.
  2. F. A. Oliehoek and C. Amato. A Concise Introduction to Decentralized POMDPs. SpringerBriefs in Intelligent Systems. Springer, 2016
  3. Canova, F. B. E. Hansen (1995), "Are seasonal patterns constant over time? A test for seasonal stability," Journal of Business and Economic Statistics, 13, 237–252.
  4. V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.
  5. Barrett, C. B. (1997), "Heteroscedastic price forecasting for food security management in developing countries," Oxford Development Studies, 25, 225–236.
  6. R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.
  7. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., When to Sell and When to Hold FTNT Stock. AC Investment Research Journal, 101(3).
Frequently Asked QuestionsQ: What is the prediction methodology for SSAAW stock?
A: SSAAW stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and ElasticNet Regression
Q: Is SSAAW stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes SSAAW Stock.
Q: Is Science Strategic Acquisition Corp. Alpha Warrant stock a good investment?
A: The consensus rating for Science Strategic Acquisition Corp. Alpha Warrant is Wait until speculative trend diminishes and assigned short-term Ba2 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of SSAAW stock?
A: The consensus rating for SSAAW is Wait until speculative trend diminishes.
Q: What is the prediction period for SSAAW stock?
A: The prediction period for SSAAW is (n+1 year)

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